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Related Experiment Video

Updated: Jul 13, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Nowcasting tourist nights spent using innovative human mobility data.

Umberto Minora¹, Stefano Maria Iacus², Filipe Batista E Silva¹

¹European Commission, Joint Research Centre, Ispra, Italy.

|October 13, 2023

Summary

This summary is machine-generated.

Google Community Mobility Reports can nowcast tourism demand with high accuracy. This novel data source offers timely insights for tourism statistics, aiding management despite privacy concerns.

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Area of Science:

Tourism research
Data science
Spatio-temporal analytics

Background:

Tourism statistics often lag behind dynamic demand, especially during crises.
Timely data is crucial for effective tourism monitoring and management.
Alternative data sources like digital traces offer potential solutions.

Purpose of the Study:

To explore the potential of Google Community Mobility Reports for nowcasting tourism demand.
To assess the accuracy of human mobility data in predicting monthly hotel nights at a sub-national level.
To compare the efficacy of mobility data against web search and mobile phone data for tourism analytics.

Main Methods:

Utilized machine learning models to analyze human mobility data.
Focused on 11 European countries from 2020 to mid-2022.
Compared predictive performance with traditional and alternative data sources.

Main Results:

Human mobility data demonstrated high accuracy in nowcasting tourism demand (monthly nights spent).
Google Community Mobility Reports showed significant potential for real-time tourism statistics.
Performance was competitive when compared to web search and mobile phone data.

Conclusions:

Human mobility data offers a viable, accurate, and timely alternative for tourism demand forecasting.
This facilitates more frequent and responsive tourism statistics production.
Privacy and surveillance issues remain challenges for widespread adoption.